Laurence Yang

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Optimization & Training — 8 citations into it

Whom Laurence Yang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. James Martens

Papers from Laurence Yang's perspective

Ordered by how strongly the researchers Laurence Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Long Short-Term Memory
3. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
4. On the importance of initialization and momentum in deep learning
5. Deep learning via Hessian-free optimization
6. Deep Learning
7. Optimizing Neural Networks with Kronecker-factored Approximate Curvature
8. Some methods of speeding up the convergence of iteration methods
9. Learning Recurrent Neural Networks with Hessian-Free Optimization
10. Stochastic Gradient Learning in Neural Networks

Their papers

• Revisiting Recursive Least Squares for Training Deep Neural Networks (2021) — 7 citations